Deploying to main from @ ivy-llc/ivy@46e00f5 🚀

_sources/overview/related_work/ivy_vs_onnx.rst.txt

@@ -9,8 +9,8 @@ Comparing Ivy with ONNX
 .. |onnx| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/main/img/externally_linked/related_work/exchange_formats/onnx.png
     :height: 20pt
     :class: dark-light
-.. |ivy| image:: https://raw.githubusercontent.com/ivy-llc/assets/refs/heads/main/assets/logos/ivy-long.svg
-    :height: 26pt
+.. |ivy| image:: https://raw.githubusercontent.com/ivy-llc/assets/refs/heads/main/assets/logos/ivy-long.png
+    :height: 40pt
     :class: dark-light
 
 ONNX |onnx|

docs/functional/ivy/ivy.functional.ivy.meta.html

@@ -1334,7 +1334,7 @@ <h1>Meta<a class="headerlink" href="#meta" title="Link to this heading">#</a></h
 <li><p><strong>variables</strong> (<a class="reference internal" href="../../data_classes/data_classes/ivy.data_classes.container.html#ivy.data_classes.container.container.Container" title="ivy.data_classes.container.container.Container"><code class="xref py py-class docutils literal notranslate"><span class="pre">Container</span></code></a>) – Variables to be optimized during the meta step</p></li>
 <li><p><strong>inner_grad_steps</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code>) – Number of gradient steps to perform during the inner loop.</p></li>
 <li><p><strong>inner_learning_rate</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code>) – The learning rate of the inner loop.</p></li>
-<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7fd9547708b0&gt;</span></code>) – The function used for the inner loop optimization.
+<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f95b8ebc8b0&gt;</span></code>) – The function used for the inner loop optimization.
 Default is ivy.gradient_descent_update.</p></li>
 <li><p><strong>inner_batch_fn</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code>[<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>], default: <code class="docutils literal notranslate"><span class="pre">None</span></code>) – Function to apply to the task sub-batch, before passing to the inner_cost_fn.
 Default is <code class="docutils literal notranslate"><span class="pre">None</span></code>.</p></li>
@@ -1388,7 +1388,7 @@ <h1>Meta<a class="headerlink" href="#meta" title="Link to this heading">#</a></h
 <li><p><strong>variables</strong> (<a class="reference internal" href="../../data_classes/data_classes/ivy.data_classes.container.html#ivy.data_classes.container.container.Container" title="ivy.data_classes.container.container.Container"><code class="xref py py-class docutils literal notranslate"><span class="pre">Container</span></code></a>) – Variables to be optimized during the meta step</p></li>
 <li><p><strong>inner_grad_steps</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code>) – Number of gradient steps to perform during the inner loop.</p></li>
 <li><p><strong>inner_learning_rate</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code>) – The learning rate of the inner loop.</p></li>
-<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7fd9547708b0&gt;</span></code>) – The function used for the inner loop optimization.
+<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f95b8ebc8b0&gt;</span></code>) – The function used for the inner loop optimization.
 Default is ivy.gradient_descent_update.</p></li>
 <li><p><strong>inner_batch_fn</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code>[<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>], default: <code class="docutils literal notranslate"><span class="pre">None</span></code>) – Function to apply to the task sub-batch, before passing to the inner_cost_fn.
 Default is <code class="docutils literal notranslate"><span class="pre">None</span></code>.</p></li>
@@ -1465,7 +1465,7 @@ <h1>Meta<a class="headerlink" href="#meta" title="Link to this heading">#</a></h
 <li><p><strong>variables</strong> (<a class="reference internal" href="../../data_classes/data_classes/ivy.data_classes.container.html#ivy.data_classes.container.container.Container" title="ivy.data_classes.container.container.Container"><code class="xref py py-class docutils literal notranslate"><span class="pre">Container</span></code></a>) – Variables to be optimized.</p></li>
 <li><p><strong>inner_grad_steps</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code>) – Number of gradient steps to perform during the inner loop.</p></li>
 <li><p><strong>inner_learning_rate</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code>) – The learning rate of the inner loop.</p></li>
-<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7fd9547708b0&gt;</span></code>) – The function used for the inner loop optimization. It takes the learnable
+<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f95b8ebc8b0&gt;</span></code>) – The function used for the inner loop optimization. It takes the learnable
 weights,the derivative of the cost with respect to the weights, and the learning
 rate as arguments, and returns the updated variables.
 Default is <cite>gradient_descent_update</cite>.</p></li>

docs/functional/ivy/meta/ivy.functional.ivy.meta.fomaml_step.html

@@ -1337,7 +1337,7 @@ <h1>fomaml_step<a class="headerlink" href="#fomaml-step" title="Link to this hea
 <li><p><strong>variables</strong> (<a class="reference internal" href="../../../data_classes/data_classes/ivy.data_classes.container.html#ivy.data_classes.container.container.Container" title="ivy.data_classes.container.container.Container"><code class="xref py py-class docutils literal notranslate"><span class="pre">Container</span></code></a>) – Variables to be optimized during the meta step</p></li>
 <li><p><strong>inner_grad_steps</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code>) – Number of gradient steps to perform during the inner loop.</p></li>
 <li><p><strong>inner_learning_rate</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code>) – The learning rate of the inner loop.</p></li>
-<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7fd9547708b0&gt;</span></code>) – The function used for the inner loop optimization.
+<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f95b8ebc8b0&gt;</span></code>) – The function used for the inner loop optimization.
 Default is ivy.gradient_descent_update.</p></li>
 <li><p><strong>inner_batch_fn</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code>[<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>], default: <code class="docutils literal notranslate"><span class="pre">None</span></code>) – Function to apply to the task sub-batch, before passing to the inner_cost_fn.
 Default is <code class="docutils literal notranslate"><span class="pre">None</span></code>.</p></li>

docs/functional/ivy/meta/ivy.functional.ivy.meta.maml_step.html

@@ -1337,7 +1337,7 @@ <h1>maml_step<a class="headerlink" href="#maml-step" title="Link to this heading
 <li><p><strong>variables</strong> (<a class="reference internal" href="../../../data_classes/data_classes/ivy.data_classes.container.html#ivy.data_classes.container.container.Container" title="ivy.data_classes.container.container.Container"><code class="xref py py-class docutils literal notranslate"><span class="pre">Container</span></code></a>) – Variables to be optimized during the meta step</p></li>
 <li><p><strong>inner_grad_steps</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code>) – Number of gradient steps to perform during the inner loop.</p></li>
 <li><p><strong>inner_learning_rate</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code>) – The learning rate of the inner loop.</p></li>
-<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7fd9547708b0&gt;</span></code>) – The function used for the inner loop optimization.
+<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f95b8ebc8b0&gt;</span></code>) – The function used for the inner loop optimization.
 Default is ivy.gradient_descent_update.</p></li>
 <li><p><strong>inner_batch_fn</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code>[<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>], default: <code class="docutils literal notranslate"><span class="pre">None</span></code>) – Function to apply to the task sub-batch, before passing to the inner_cost_fn.
 Default is <code class="docutils literal notranslate"><span class="pre">None</span></code>.</p></li>

docs/functional/ivy/meta/ivy.functional.ivy.meta.reptile_step.html

@@ -1334,7 +1334,7 @@ <h1>reptile_step<a class="headerlink" href="#reptile-step" title="Link to this h
 <li><p><strong>variables</strong> (<a class="reference internal" href="../../../data_classes/data_classes/ivy.data_classes.container.html#ivy.data_classes.container.container.Container" title="ivy.data_classes.container.container.Container"><code class="xref py py-class docutils literal notranslate"><span class="pre">Container</span></code></a>) – Variables to be optimized.</p></li>
 <li><p><strong>inner_grad_steps</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code>) – Number of gradient steps to perform during the inner loop.</p></li>
 <li><p><strong>inner_learning_rate</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code>) – The learning rate of the inner loop.</p></li>
-<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7fd9547708b0&gt;</span></code>) – The function used for the inner loop optimization. It takes the learnable
+<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f95b8ebc8b0&gt;</span></code>) – The function used for the inner loop optimization. It takes the learnable
 weights,the derivative of the cost with respect to the weights, and the learning
 rate as arguments, and returns the updated variables.
 Default is <cite>gradient_descent_update</cite>.</p></li>

docs/helpers/ivy_tests.test_ivy.helpers.globals.html

@@ -1323,7 +1323,7 @@
 <p>Should not be used inside any of the test functions.</p>
 <dl class="py data">
 <dt class="sig sig-object py" id="ivy_tests.test_ivy.helpers.globals.CURRENT_FRONTEND_CONFIG">
-<span class="sig-prename descclassname"><span class="pre">ivy_tests.test_ivy.helpers.globals.</span></span><span class="sig-name descname"><span class="pre">CURRENT_FRONTEND_CONFIG</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">&lt;object</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7fd947701dc0&gt;</span></em><a class="headerlink" href="#ivy_tests.test_ivy.helpers.globals.CURRENT_FRONTEND_CONFIG" title="Link to this definition">#</a></dt>
+<span class="sig-prename descclassname"><span class="pre">ivy_tests.test_ivy.helpers.globals.</span></span><span class="sig-name descname"><span class="pre">CURRENT_FRONTEND_CONFIG</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">&lt;object</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f95abdfdde0&gt;</span></em><a class="headerlink" href="#ivy_tests.test_ivy.helpers.globals.CURRENT_FRONTEND_CONFIG" title="Link to this definition">#</a></dt>
 <dd></dd></dl>
 
 <dl class="py exception">